Lead AI Research Engineer Embodied Systems

Skills

About the Role

You will own the engineering of the embodied systems stack, including onboard AI inference, data collection, teleoperation, and on-robot reinforcement learning. You will set technical direction, deploy and evaluate policies on physical robots, improve real-time reliability, align system interfaces, and mentor engineers.

Requirements

• Bachelor's or Master's degree in Computer Science, Robotics, Electrical Engineering, or a related field with significant relevant experience, or a PhD
• Track record of leading complex robotic or embodied systems end-to-end
• Proficiency in C++ and Python
• Systems programming and real-time performance-critical engineering skills
• Experience with ROS or ROS2 and robot middleware
• Experience integrating and deploying ML models or policies into real-time robotic or autonomous systems
• Ability to work in office five days per week

Responsibilities

• Lead and own onboard AI inference, data collection, teleoperation, and on-robot reinforcement learning systems
• Set the technical direction and architecture for running, evaluating, and improving learned models on robots
• Deliver embodied systems end-to-end on physical robots
• Own on-robot deployment and closed-loop policy evaluation
• Align interfaces and priorities across robotics software and ML research
• Mentor engineers and raise the technical bar for embodied systems

Benefits

• Stock options or equity programs
• Health, dental, and vision insurance
• 401(k) plan
• Visa sponsorship and green card support for qualified candidates
• Lunches and dinners
• Fully stocked kitchen
• Regular team-building events